The salivary proteome in relation to oral mucositis in autologous hematopoietic stem cell transplantation recipients: a labelled and label-free proteomics approach

Background Oral mucositis is a frequently seen complication in the first weeks after hematopoietic stem cell transplantation recipients which can severely affects patients quality of life. In this study, a labelled and label-free proteomics approach were used to identify differences between the salivary proteomes of autologous hematopoietic stem cell transplantation (ASCT) recipients developing ulcerative oral mucositis (ULC-OM; WHO score ≥ 2) or not (NON-OM). Methods In the TMT-labelled analysis we pooled saliva samples from 5 ULC-OM patients at each of 5 timepoints: baseline, 1, 2, 3 weeks and 3 months after ASCT and compared these with pooled samples from 5 NON-OM patients. For the label-free analysis we analyzed saliva samples from 9 ULC-OM and 10 NON-OM patients at 6 different timepoints (including 12 months after ASCT) with Data-Independent Acquisition (DIA). As spectral library, all samples were grouped (ULC-OM vs NON-OM) and analyzed with Data Dependent Analysis (DDA). PCA plots and a volcano plot were generated in RStudio and differently regulated proteins were analyzed using GO analysis with g:Profiler. Results A different clustering of ULC-OM pools was found at baseline, weeks 2 and 3 after ASCT with TMT-labelled analysis. Using label-free analysis, week 1–3 samples clustered distinctly from the other timepoints. Unique and up-regulated proteins in the NON-OM group (DDA analysis) were involved in immune system-related processes, while those proteins in the ULC-OM group were intracellular proteins indicating cell lysis. Conclusions The salivary proteome in ASCT recipients has a tissue protective or tissue-damage signature, that corresponded with the absence or presence of ulcerative oral mucositis, respectively. Trial registration The study is registered in the national trial register (NTR5760; automatically added to the International Clinical Trial Registry Platform). Supplementary Information The online version contains supplementary material available at 10.1186/s12903-023-03190-w.

The reaction was stopped by 15 min incubation at RT with 8 µl of 5% hydroxylamine. After labelling, all samples were mixed, incubated for 15 min at RT and freeze dried (Speed vac, -80 °C).
Before isoelectric focusing samples were resuspended in resuspension buffer (IPG stock solution), vortexed and centrifuged for 1 min at 14000 rpm. Equal volumes of each samples was added for the isoelectric focusing in low resolution 12-well strip with a 3-10 non-linear gradient. Fractions 1 and 7, fractions 2 and 8, etc. were combined to yield 6 samples for LC/MS/MS analysis. Using C18 reversedphase Zip-Tips (Millipore) glycerol was removed from the samples.
Peptides were chromatographically separated using a 75 µm C18 column (EASY NanoLC system, ThermoFisherScientific, UK) using a three step linear gradient of CAN in 0.1% formic acid. Peptides were eluted at a flow of 300 nl/min for 120 min which ionized by electrospray ionization using an Orbitrap Velos Pro operating under Xcalibur v2.2 (ThermoFisherScientific, UK). Precursor ions were selected for peptide identification and reporter ion fragmentation based on their intensity in an automated data-dependent switching mode and Higher-energy C-trap dissociation (Top 10 method).
The MS/MS analyses were conducted using higher than normal collision energy profiles that were chosen based on the m/z ratio and the charge state of the peptide. In the output, the values under ratios were Log2 transformed and used for data analysis. The principal component analysis (PCA) was performed using the 'princomp' function in RStudio. The heatmap was generated using the heatmap.2 function where the distance was calculated using a correlation measurement (equation 3 as described in Key (2012)) and the colors were scaled per row.

LFQ experiment
Sample preparation. 100 µg of pooled samples from OM and non-OM patients were added to solid urea obtaining a final concentration of 8 M urea. 20 mM HEPES pH 8.0 was added until a volume of 100 µl was reached. First, proteins were reduced through incubation for 30 minutes at 55˚C with 15 mM DTT. Next alkylation was done by incubating for 15 minutes at room temperature in the dark with 30 mM iodoacetamide. Following dilution with 20 mM HEPES pH 8.0 up to 4M urea, proteins were digested with 1 µg lysyl endopeptidase (Wako) (1/100, w/w) for 4 hours at 37°C. Samples were further diluted with 20 mM HEPES pH 8.0 to a final urea concentration of 2 M and proteins were digested with 1 µg trypsin (Promega) (1/100, w/w) overnight at 37˚C. The resulting peptide mixture was purified using OMIX C18 pipette tips (Agilent). The eluent was divided in two aliquots , dried completely by vacuum drying and stored at -20°C until further use.
Off-line high pH reversed phase C18 peptide fractionation. Prior to LC-MS/MS analysis, one aliquot of each sample was fractionated using reversed-phase chromatography at pH 5.5 using an Agilent 1100 series HPLC. A volume corresponding to 50 µg peptide material was trapped for 16 minutes using a reversed-phase trapping column (35 mm x 300 µm I.D., 5 µm beads C18 material (Dr. Maisch, Germany), fritted and packed in-house). Next each sample was separated on an analytical column (150 mm x 250 µm I.D., 3 µm beads C18 material (Dr. Maisch, Germany), fritted and packed in-house) using a 100 min gradient from 100% solvent A (10 mM ammonium acetate, pH 5.5) to 100% solvent B (10 mM ammonium acetate, 70% ACN, pH 5.5) at a constant flow rate of 3 µL/min. The mass tolerance for precursor and fragment ions was set to 4.5 and 20 ppm, respectively, during the main search. Enzyme specificity was set as C-terminal to arginine and lysine (trypsin), also allowing cleavage at arginine/lysine-proline bonds with a maximum of two missed cleavages.
Carbamidomethylation of cysteine residues was set as a fixed modification and variable modifications were set to oxidation of methionine residues (to sulfoxides) and acetylation of protein N-termini.
Proteins were quantified by the MaxLFQ algorithm integrated in the MaxQuant software (PMID 24942700). Only proteins with at least one unique or razor peptide were retained for identification, while a minimum ratio count of two unique peptides was required for quantification.